CN114889625A - Method for establishing vehicle following model at road curve based on safe potential field theory - Google Patents

Method for establishing vehicle following model at road curve based on safe potential field theory Download PDF

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CN114889625A
CN114889625A CN202210625677.9A CN202210625677A CN114889625A CN 114889625 A CN114889625 A CN 114889625A CN 202210625677 A CN202210625677 A CN 202210625677A CN 114889625 A CN114889625 A CN 114889625A
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vehicle
road
automatic driving
potential field
curve
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于斌
杭子承
王书易
任小乐
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Southeast University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0018—Method for the design of a control system
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • B60W2050/0034—Multiple-track, 2D vehicle model, e.g. four-wheel model
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/30—Road curve radius
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

Abstract

The invention discloses a method for establishing an automatic driving car following model based on a two-dimensional plane at a road curve of a safe potential field theory, which comprises the following steps of: acquiring geometric linear information of roads at road curves, information of automatic driving vehicles and information of vehicles in traffic flow; the method comprises the steps of establishing a two-dimensional plane physical mechanical function of an automatic driving vehicle at a road curve, establishing a two-dimensional plane potential field model and a road potential field model according to a safety potential field theory, obtaining the speed and the acceleration of the automatic driving vehicle at the curve and a vehicle ahead through the physical mechanical function, overlapping the vehicle potential field and the road potential field, and finally establishing a curve safety potential field following model of the automatic driving vehicle. The method can effectively evaluate the driving risk of the following behavior of the automatic driving vehicle at the road curve, and carries out the potential safety hazard investigation on the popularization of the automatic driving vehicle and the actual operation of the existing road infrastructure.

Description

Method for establishing vehicle following model at road curve based on safe potential field theory
Technical Field
The invention relates to a method for establishing an automatic driving vehicle following model based on a two-dimensional plane at a road curve of a safety potential field theory, and belongs to the technical field of road safety evaluation.
Background
An autonomous and connected vehicle (ICV) is a vehicle with advanced vehicle-mounted sensors,The system comprises a controller, an actuator and other devices, integrates modern communication and network technologies, realizes intelligent information exchange and sharing between vehicles and X (vehicles, roads, people, clouds and the like), has the functions of complex environment perception, intelligent decision, cooperative control and the like, can realize safe, efficient, comfortable and energy-saving driving, and finally realizes a new generation of automobiles operated by replacing people [1-5] . The intelligent networked automobile can provide a safer, more energy-saving, more environment-friendly and more convenient travel mode and a comprehensive solution, and is an internationally recognized future development direction and focus of attention.
In a complex traffic system, in the face of a variable road traffic environment, vehicles running on the road make different driving behavior responses according to traffic information obtained by the vehicles. The differences in the driving behavior of different vehicles are often the main factors affecting road traffic safety and road traffic efficiency. During the running process of the vehicle, different driving behaviors are selected mainly according to the expected speed of the vehicle and the safe distance between the vehicle and the surrounding vehicle. The following behavior (following) and the lane changing behavior (lane changing) are 2 basic driving behaviors in the driving process of the vehicle, so that the following model and the lane changing model in the traditional traffic flow theory achieve detailed description of the following behavior and the lane changing behavior of the vehicle by analyzing the longitudinal and transverse interaction of the vehicle in the driving process of the road. During the running of the autonomous vehicle, the autonomous vehicle makes a selection of following or lane changing based on its desired speed and information (position, speed, etc.) of the nearby vehicle. Compared with the following behavior of a driver driving the vehicle, the following behavior process is more complicated, the influence of the running track of the surrounding vehicles is more obvious, and the research significance of the safety is more obvious. In recent years, the development of autonomous driving has provided new opportunities and challenges for traffic management and control. The automatic driving automobile can realize information interaction among vehicles through a vehicle-mounted sensor, a controller, an actuator and the like, and complete the following behavior. However, considering the change of the relevant road alignment condition and environment and the interaction between the intelligent internet vehicle and the traffic flow, the safety problem of the automatic driving vehicle running on the road is the research object of a plurality of scholars at present.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the automatic driving vehicle following model based on the two-dimensional plane at the road curve of the safety potential field theory is beneficial to evaluating the driving risk of the automatic driving vehicle following behavior at the road curve, provides theoretical reference for the optimization of the early warning function design of the conditional automatic driving system, and carries out potential safety hazard investigation for the function test of the conditional automatic driving system and the actual operation of the existing road infrastructure.
The invention adopts the following technical scheme for solving the technical problems:
a safety potential field theory-based automatic driving vehicle following risk model at a road curve comprises the following steps:
step 1, acquiring running condition information of an automatic driving vehicle at a road curve in a traffic flow, wherein the running condition information comprises road geometric and linear information, front vehicle information and automatic driving vehicle information;
step 2, establishing a two-dimensional space coordinate axis of a road cross section at a road curve, and depicting the following behavior of the automatic driving vehicle at the road curve;
step 3, establishing a physical and mechanical function of the following behavior of the automatic driving vehicle at the cross section of the road;
step 4, respectively establishing a road potential field model and a vehicle potential field model according to a safety potential field theory;
and 5, establishing a following model of the automatic driving vehicle at the road curve based on the safe potential field theory.
As a preferable aspect of the present invention, the road geometric alignment information in step 1 includes: the road curve comprises a road curve turning radius and a road surface width, wherein the road turning radius comprises an inner side road boundary radius and an outer side road boundary radius; the front vehicle information comprises the traction force of the front vehicle and the steering angle of the front vehicle; the autonomous vehicle information includes an autonomous vehicle tractive effort magnitude, an autonomous vehicle steering angle, and a relative distance of an autonomous vehicle center of mass to a front vehicle center of mass.
As a preferred embodiment of the present invention, the specific process of step 2 is as follows:
step 21, making the inside and outside curve line shapes of the road according to the obtained geometric line shape information of the road curve, obtaining the position of a road center line according to the inside road radius and the outside road boundary radius of the road curve, setting the starting point of the road center line at the road curve as a coordinate origin, setting the driving direction of an automatic driving vehicle and a front vehicle as the positive direction of a coordinate axis, and establishing a two-dimensional space coordinate axis of the road cross section;
and step 22, marking the coordinate information of the front vehicle and the automatic driving vehicle according to the positions of the centers of mass of the front vehicle and the automatic driving vehicle on the basis of the coordinate axis established in the step 21, and obtaining the distance information between the centers of mass of the two vehicles through a sensor on the automatic driving vehicle. Setting A vehicle as front vehicle, B vehicle as automatic driving vehicle, d AB Is the distance between the vehicle in front and the autonomous vehicle.
As a preferred embodiment of the present invention, the specific process of step 3 is as follows:
step 31, when the automatic driving vehicle B runs along a curve of a road, according to the requirement of mechanical balance of a two-dimensional space plane, the automatic driving vehicle B is acted by traction force and centripetal force, and the mechanical function expression is as follows: f 1 ＝M B a B
Figure BDA0003677261230000031
In the formula: f 1 Traction for autonomous vehicle B; f 2 Centripetal force experienced at a road curve for the autonomous vehicle B; m B Gravity for autonomous vehicle B; a is a B Acceleration in the traveling direction of the autonomous vehicle B; v. of B Speed in the direction of travel for autonomous vehicle B; r is the turning radius of the road curve;
and step 32, obtaining the steering angle of the automatic driving vehicle B running along the curve according to the traction force and the centripetal force received by the automatic driving vehicle B as follows:
Figure BDA0003677261230000032
and step 33, obtaining the resultant force of the centripetal force and the traction force of the automatic driving vehicle B at the road curve according to the steering angle of the automatic driving vehicle B obtained by the inverse calculation of the traction force and the centripetal force in the step 32:
Figure BDA0003677261230000033
and step 34, obtaining the acceleration of the automatic driving vehicle B in the resultant force direction at the curve according to the magnitude of the resultant force received by the automatic driving vehicle B at the curve of the road obtained in the step 33 as follows:
Figure BDA0003677261230000034
step 35, similarly, obtaining the acceleration of the front vehicle a in the direction of the resultant force at the curve as:
Figure BDA0003677261230000035
in the formula: f 1 ' is the traction of the vehicle a in front; f 2 ' is the centripetal force experienced by the vehicle a ahead at a road curve; m A Is the gravity of the preceding vehicle a; a is A Acceleration in the traveling direction of the preceding vehicle a; v. of A The speed of the preceding vehicle a in the traveling direction; theta' is the steering angle of the front vehicle A along the curve; f Combination of Chinese herbs ' is the resultant of centripetal and tractive force of the vehicle a ahead at the road curve.
As a preferred embodiment of the present invention, the specific process of step 4 is as follows:
step 41, road traffic is composed of basic elements such as people, vehicles, roads, environment and the like, the total safety potential field of the road is the superposition of the self safety potential fields of a plurality of traffic elements, and the influence of the road boundary field is caused because the vehicles are always in a following state in the turning processSmaller, the superposition of the road potential field and the vehicle potential field is mainly received at the road curve under the following state of the automatic driving vehicle, so the potential field intensity E of the safe total potential field in the scene total The calculation is as follows:
|E total |＝ω L |E L |+ω s |E s |+ω v |E V |
in the formula: e L Is the potential field strength of the road line field; e s Is road boundary potential field strength; e V A potential field strength being a vehicle potential field; omega L 、ω S 、ω V The weights are respectively assigned to the potential field strength of the road line field, the potential field strength of the road boundary field, and the potential field strength of the vehicle potential field.
Step 42, since the automatic driving vehicle B does not deviate from the road center line to drive in the center driving process of the single lane road under the ideal state of the following model, and the effect of the road line field potential field is negligible, the potential field intensity expression of the safety total potential field in the scene is as follows:
|E total |＝ω S |E s |+ω v |E V |
and 43, calculating the potential field size of the road boundary field according to the expression of the safety total potential field in the step 42:
Figure BDA0003677261230000041
d S Aj ＝(y s,j -y A )
in the formula: d S Aj A distance vector for the leading vehicle A to point to the road boundary line; d S Aj ＝(y s,j -y A )；y A Is the y-axis coordinate of the front vehicle A; y is s Is the y-axis coordinate of the road line field j; eta is the road boundary field coefficient.
Step 44, calculating the autonomous vehicle potential field E according to the expression of the safety total potential field in step 42 V The position coordinate of the center of mass of the autonomous vehicle B in the two-dimensional space coordinate system is (x) 0 ,y 0 ) In a following scene, the distance k from a two-dimensional plane space point to the vehicle has the following relationship:
Figure BDA0003677261230000042
step 46, according to the formula from the space point to the center of mass of the autonomous vehicle in step 45, considering that the follow-up running of the autonomous vehicle is realized only on a two-dimensional space plane, and not considering the velocity component generated in the vertical direction, in order to better describe the change of the degree of risk faced by the autonomous vehicle B when approaching the front vehicle, the distance correction is performed on the distance of the actual two-dimensional space:
Figure BDA0003677261230000043
Figure BDA0003677261230000044
in the formula: k' is a pseudo distance; θ is a steering angle at which the vehicle is steered (the counterclockwise direction of the predetermined steering angle is a positive steering angle direction); (x) * ,y * ) And obtaining a corresponding deflection value after the original coordinate (x, y) is deflected.
And step 47, according to the two-dimensional space plane pseudo-distance formula in step 46, the influence of the vehicle potential field formed by the automatic driving vehicle on the vehicles around the target vehicle has the following effects due to the influence of the potential fields of other vehicles around the automatic driving vehicle: when the surrounding vehicle is a certain distance away from the automatic driving vehicle, the vehicle potential field of the target vehicle acts on the surrounding vehicle, and therefore the automatic driving vehicle potential field model is constructed as follows:
Figure BDA0003677261230000051
in the formula: lambda, beta 1 Are all undetermined coefficients; a is Combination of Chinese herbs Acceleration in the direction of travel of the autonomous vehicle;
Figure BDA0003677261230000052
the included angle between the driving direction of the automatic driving vehicle and the connecting line of the mass center of the automatic driving vehicle and the front vehicle is formed.
As a preferred south of the present invention, the specific process of step 5 is as follows:
step 51, according to the safety potential field theory, the magnitude of the potential field force of the front vehicle on the automatic driving vehicle can be expressed as:
Figure BDA0003677261230000053
in the formula: : Δ x is the distance between the center of mass of the autonomous vehicle B and the center of mass of the forward vehicle a; e V ' is the potential field intensity of the front vehicle; m A 、M B Mass of the autonomous vehicle and the preceding vehicle, respectively; lambda, beta 1 、β 2 Are all undetermined coefficients.
Step 52, due to the field force F AB Is the reason for changing the acceleration and deceleration in the following process of the automatic driving vehicle B, so that the vehicle B is subjected to the field force F AB Acceleration a generated under the action of AB The following were used:
Figure BDA0003677261230000054
step 53, generating common acceleration a under the action of the acceleration of the automatic driving vehicle and the potential field force of the front vehicle Field(s) (i.e., the vector sum in the direction of travel of the autonomous vehicle B) is:
Figure BDA0003677261230000055
in the formula: a is Combination of Chinese herbs Acceleration in a direction of travel for the autonomous vehicle; a is a AB Acceleration generated by a front vehicle under the action of the potential field force of the automatic driving vehicle:
Figure BDA0003677261230000056
the included angle between the driving direction of the automatic driving vehicle and the connecting line of the mass centers of the two vehicles is formed;
Figure BDA0003677261230000057
the included angle between the driving direction of the front vehicle and the connecting line of the mass centers of the two vehicles is formed; d AB Is the distance between the autonomous vehicle and the center of mass of the vehicle ahead; mu is the reduction coefficient of the acceleration generated by the potential field force along with the change of the distance.
Since the force generated by the safety potential field is of short range, i.e. it only works for short distances, the acceleration and deceleration of the vehicle when the front and rear vehicles are far apart in the following situation is mainly expressed by the relation between the current speed and the desired speed of the vehicle as follows:
a B ＝a max tanh[δ(v 0 (a) -v B )]
in the formula: a is B Acceleration of the vehicle in the event that the road and vehicle potential field forces are not functional; a is a max Is the maximum acceleration of the vehicle; v. of 0 (a) A desired speed for the vehicle under the current acceleration condition; δ is a coefficient value of the difference between the current speed and the desired speed of the vehicle.
And step 54, obtaining a following model of the two-dimensional space plane at the curve of the automatic driving vehicle based on the safe potential field theory in conclusion:
Figure BDA0003677261230000062
Figure BDA0003677261230000061
compared with the prior art, the technical scheme adopted by the invention has the following technical effects:
the method is based on the angle of the safety influence of traffic flow conditions and road conditions on vehicles in the traffic flow, the following behavior of a single-lane single automatic driving vehicle at a curve is considered by combining a safety potential field theory, the physical mechanical function of the automatic driving vehicle is established, the speed and the acceleration of the following behavior of the automatic driving vehicle are estimated by a potential field model of the automatic driving vehicle and a road potential field model under the comprehensive safety potential field theory, a complete automatic driving vehicle following model under the safety potential field theory is obtained, and theoretical reference is provided for the safety problem of the automatic driving vehicle under the actual road scene. Meanwhile, the method for acquiring the following risk of the automatic driving vehicle is used for popularizing the automatic driving vehicle and carrying out potential safety hazard investigation on the actual operation of the existing road infrastructure.
Drawings
FIG. 1 is a flow chart of an automatic driving vehicle following model based on a two-dimensional plane at a road curve of a safe potential field theory according to the invention;
fig. 2 is a diagram of the physical-mechanical function of the following behavior of an autonomous vehicle according to the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention provides a method for establishing an automatic driving vehicle following model based on a two-dimensional plane at a road curve of a safe potential field theory, which comprises the following specific steps as shown in figure 1:
(1) acquiring geometric and linear information of a road, information of an automatic driving vehicle and information of a front vehicle;
the road geometric alignment information at the curve comprises: the road curve comprises a road curve turning radius and a road surface width, wherein the road turning radius comprises an inner side road boundary radius and an outer side road boundary radius; the front vehicle information comprises the magnitude of vehicle traction, a front vehicle steering angle and the position in a front vehicle coordinate axis; the autonomous vehicle information includes a magnitude of tractive effort of the autonomous vehicle, a steering angle of the autonomous vehicle, a position in a coordinate axis of the autonomous vehicle, and a relative distance to a center of mass of the lead vehicle.
(2) Establishing a two-dimensional space coordinate axis of a road plane;
1) the road curve information is used for obtaining the position of a road center line according to the radius of an inner road and an outer road of the road curve, and the starting point of the road center line is set as the origin of coordinates to establish a two-dimensional space coordinate axis of a road plane as shown in figure 2.
2) Marking the coordinate information of the front vehicle and the automatic driving vehicle according to the positions of the centers of mass of the front vehicle and the automatic driving vehicle on the basis of the coordinate axis established in the step 1), and obtaining the distance information between the centers of mass of the two vehicles through a sensor on the automatic driving vehicle.
(3) Establishing a physical mechanical function of the automatic driving vehicle and the front vehicle;
1) when the automatic driving vehicle B runs along a curve of a road, the automatic driving vehicle B is acted by traction force and centripetal force according to the mechanical balance requirement of a two-dimensional plane, and the mechanical function expression is as follows:
F 1 ＝M B a B
Figure BDA0003677261230000071
in the formula: f 1 Traction for autonomous vehicle B; f 2 Centripetal force experienced at a road curve for the autonomous vehicle B; m B Gravity for autonomous vehicle B; a is B Acceleration in the traveling direction of the autonomous vehicle B; v is the speed of the autonomous vehicle B in the direction of travel at this point; r is the turning radius at the bend;
2) the steering angle of the automatic driving vehicle B along the curve is obtained according to the traction force and the centripetal force received by the automatic driving vehicle B:
Figure BDA0003677261230000072
3) and (3) obtaining the resultant force of the centripetal force and the traction force of the automatic driving vehicle B at the road curve according to the steering angle of the automatic driving vehicle B obtained by the inverse calculation of the traction force and the centripetal force:
Figure BDA0003677261230000073
4) according to the magnitude of the resultant force received by the automatic driving vehicle B at the road curve, the acceleration of the automatic driving vehicle B in the direction of the resultant force at the curve is obtained as follows:
Figure BDA0003677261230000074
5) similarly, a physical and mechanical model of the front vehicle a is obtained according to the above steps, and the acceleration of the front vehicle a in the direction of the resultant force at the curve is:
Figure BDA0003677261230000075
(4) establishing a road potential field and vehicle potential field model;
1) the road traffic is composed of basic elements such as people, vehicles, roads, environment and the like, the road total safety potential field is the superposition of self safety potential fields of a plurality of traffic elements, the influence of a road boundary field is small because vehicles are always in a following state in the turning process, and the potential field intensity E of the safety total potential field in the scene is mainly superposed by the road potential field and the vehicle potential field at the road curve under the following state of an automatic driving vehicle total The calculation is as follows:
|E total |＝ω L |E L |+ω S |E S |+ω V |E V |
in the formula: e L Is the potential field strength of the road line field; e s Is road boundary potential field strength; e V A potential field strength being a vehicle potential field; omega L 、ω S 、ω V The weights are respectively assigned to the potential field strength of the road line field, the potential field strength of the road boundary field, and the potential field strength of the vehicle potential field.
2) Because the automatic driving vehicle B does not deviate from the center line of the road to drive in the center driving process of the single-lane road under the ideal state of the following model, and the effect of the road line field potential field is negligible, the potential field intensity expression of the safety total potential field in the scene is as follows:
|E total |＝ω S |E S |+ω V |E V |
3) calculating the potential field size of the road boundary field according to the safety total potential field expression:
Figure BDA0003677261230000081
d S Aj ＝(y s,j -y A )
in the formula: the y-axis coordinate of the preceding vehicle A is y A (ii) a Y-axis coordinate of the road line field j is y s ；d S Aj A distance vector for the leading vehicle A to point to the road boundary line; eta is the road boundary field coefficient.
4) Calculating the autonomous vehicle potential field E according to the expression of the safety total potential field in step 42 V The position coordinate of the center of mass of the autonomous vehicle B in the two-dimensional space coordinate system is (x) 0 ,y 0 ) In a following scene, the distance k between a two-dimensional plane space point and the vehicle has the following relation:
Figure BDA0003677261230000082
5) according to the formula from the space point to the center of mass of the automatic driving vehicle, the follow-up motion of the automatic driving vehicle is realized only on a two-dimensional plane, the velocity component generated in the vertical direction is not considered, and the distance of the actual two-dimensional space is subjected to distance correction in order to better describe the change of the risk degree of the automatic driving vehicle B when approaching the front vehicle:
Figure BDA0003677261230000083
Figure BDA0003677261230000084
in the formula: k' is a pseudo distance; θ is a steering angle at which the vehicle is steered (the counterclockwise direction of the predetermined steering angle is a steering angle positive direction); (x) * ,y * ) And obtaining a corresponding deflection value after the original coordinate (x, y) is deflected.
6) According to the above two-dimensional spatial plane pseudo-distance formula, the influence of the vehicle potential field formed by the autonomous vehicle on the vehicles around the target vehicle has the following effect due to the influence of the potential fields of other vehicles around: when the surrounding vehicle is a certain distance away from the automatic driving vehicle, the vehicle potential field of the target vehicle acts on the surrounding vehicle, and therefore the automatic driving vehicle potential field model is constructed as follows:
Figure BDA0003677261230000091
in the formula: lambda, beta 1 Are all undetermined coefficients; a is Combination of Chinese herbs Acceleration in the direction of travel of the autonomous vehicle;
Figure BDA0003677261230000092
the included angle between the driving direction of the automatic driving vehicle and the connecting line of the mass center of the automatic driving vehicle and the front vehicle is formed.
(5) Establishing an automatic driving vehicle following model of a two-dimensional plane at a road curve based on a safe potential field theory;
1) according to the safe potential field theory, the magnitude of the potential field force of the vehicle in front of the autonomous vehicle can be expressed as:
Figure BDA0003677261230000093
in the formula: e V ' is the front vehicle potential field intensity; m A 、M B Mass of the autonomous vehicle and the preceding vehicle, respectively; lambda, beta 1 、β 2 Are all undetermined coefficients.
2) Due to field force F AB Is the reason for changing the acceleration and deceleration in the following process of the automatic driving vehicle B, so that the vehicle B is subjected to the field force F AB Acceleration a generated under the action of AB The following were used:
Figure BDA0003677261230000094
3) the common acceleration a is generated under the action of the acceleration of the automatic driving vehicle and the potential field force of the front vehicle Field(s) (i.e., the vector sum in the direction of travel of the autonomous vehicle B) is:
Figure BDA0003677261230000095
in the formula: a is Combination of Chinese herbs Acceleration in a direction of travel for the autonomous vehicle; a is AB Acceleration generated by a front vehicle under the action of the potential field force of the automatic driving vehicle:
Figure BDA0003677261230000096
the included angle between the driving direction of the automatic driving vehicle and the connecting line of the mass centers of the two vehicles is formed;
Figure BDA0003677261230000097
the included angle between the driving direction of the front vehicle and the connecting line of the mass centers of the two vehicles is formed; d AB Is the distance between the autonomous vehicle and the center of mass of the vehicle ahead; mu is the reduction coefficient of the acceleration generated by the potential field force along with the change of the distance.
Since the force generated by the safety potential field is of short range, i.e. it only works for short distances, the acceleration and deceleration of the vehicle when the front and rear vehicles are far apart in the following situation is mainly expressed by the relation between the current speed and the desired speed of the vehicle as follows:
a B ＝a max tanh[δ(v 0 (a) -v B )]
in the formula: a is B Acceleration of the vehicle in the event that the road and vehicle potential field forces are not functional; a is max Is the maximum acceleration of the vehicle; v. of 0 (a) A desired speed for the vehicle under the current acceleration condition; δ is a coefficient value of the difference between the current speed and the desired speed of the vehicle.
4) In conclusion, a two-dimensional plane following model of the curve of the automatic driving vehicle based on the safe potential field theory is obtained:
Figure BDA0003677261230000102
Figure BDA0003677261230000101
in summary, from the perspective of the safety influence of traffic flow conditions and road conditions on vehicles in the traffic flow, the invention considers the following behavior of a single-lane single automatic driving vehicle at a curve by combining the safety potential field theory, establishes the physical mechanical function of the automatic driving vehicle, evaluates the speed and the acceleration of the following behavior of the automatic driving vehicle by the automatic driving vehicle potential field model and the road potential field model under the safety potential field theory to obtain a complete automatic driving vehicle following model under the safety potential field theory, and provides theoretical reference for the safety problem of the automatic driving vehicle under the actual road scene. Meanwhile, the method for acquiring the following risk of the automatic driving vehicle is used for popularizing the automatic driving vehicle and carrying out potential safety hazard investigation on the actual operation of the existing road infrastructure.
The invention also provides a vehicle track change track deviation calculation device based on traffic simulation, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the method for establishing the vehicle following model at the road curve based on the safe potential field theory when executing the computer program.
The invention also provides a computer-readable storage medium on which a computer program is stored, which, when being executed by a processor, implements the steps of the above method for establishing a vehicle-following model at a road curve based on a safe potential field theory.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.

Claims (8)

1. The method for establishing the vehicle following model at the road curve based on the safe potential field theory is characterized by comprising the following steps of:
step 1, acquiring running condition information of an automatic driving vehicle at a road curve in a traffic flow, wherein the running condition information comprises road geometric and linear information, front vehicle information and automatic driving vehicle information;
step 2, establishing a two-dimensional space coordinate axis of a road cross section at a road curve, and depicting the following behavior of the automatic driving vehicle at the road curve;
step 3, establishing a physical and mechanical function of the following behavior of the automatic driving vehicle at the cross section of the road;
step 4, respectively establishing a road potential field model and a vehicle potential field model according to a safety potential field theory;
and 5, establishing a following model of the automatic driving vehicle at the road curve based on the safe potential field theory.
2. The method for establishing a vehicle-following model at a road curve based on a safe potential field theory according to claim 1, wherein in step 1, the road geometric linear shape information comprises: the road curve comprises a road curve turning radius and a road surface width, wherein the road turning radius comprises an inner side road boundary radius and an outer side road boundary radius; the front vehicle information comprises the traction force of the front vehicle and the steering angle of the front vehicle; the autonomous vehicle information includes an autonomous vehicle tractive effort magnitude, an autonomous vehicle steering angle, and a relative distance of an autonomous vehicle center of mass to a front vehicle center of mass.
3. The method for establishing a vehicle-following model at a road curve based on a safe potential field theory according to claim 1, wherein the specific process of the step 2 is as follows:
step 21, making the inside and outside curve line shapes of the road according to the obtained geometric line shape information of the road curve, obtaining the position of a road center line according to the inside road radius and the outside road boundary radius of the road curve, setting the starting point of the road center line at the road curve as a coordinate origin, setting the driving direction of an automatic driving vehicle and a front vehicle as the positive direction of a coordinate axis, and establishing a two-dimensional space coordinate axis of the road cross section;
and step 22, marking the coordinate information of the front vehicle and the automatic driving vehicle according to the positions of the centers of mass of the front vehicle and the automatic driving vehicle on the basis of the coordinate axis established in the step 21, and obtaining the distance information between the centers of mass of the two vehicles through a sensor on the automatic driving vehicle.
4. The method for establishing the vehicle-following model at the road curve based on the safe potential field theory according to claim 3, wherein the specific process of the step 3 is as follows:
step 31, when the automatic driving vehicle B runs along a curve of a road, according to the requirement of mechanical balance of a two-dimensional space plane, the automatic driving vehicle B is acted by traction force and centripetal force, and the mechanical function expression is as follows: f 1 ＝M B a B
Figure FDA0003677261220000011
In the formula: f 1 Traction for autonomous vehicle B; f 2 Centripetal force experienced at a road curve for the autonomous vehicle B; m B Gravity for autonomous vehicle B; a is B Acceleration in the traveling direction of the autonomous vehicle B; v. of B Is the speed of the autonomous vehicle B in the direction of travel; r is the turning radius of the road curve;
and step 32, obtaining the steering angle of the automatic driving vehicle B running along the curve according to the traction force and the centripetal force received by the automatic driving vehicle B as follows:
Figure FDA0003677261220000021
and step 33, obtaining the resultant force of the centripetal force and the traction force of the automatic driving vehicle B at the road curve according to the steering angle of the automatic driving vehicle B obtained by the inverse calculation of the traction force and the centripetal force in the step 32:
Figure FDA0003677261220000022
and step 34, obtaining the acceleration of the automatic driving vehicle B in the resultant force direction at the curve according to the magnitude of the resultant force received by the automatic driving vehicle B at the curve of the road obtained in the step 33 as follows:
Figure FDA0003677261220000023
step 35, similarly, obtaining the acceleration of the front vehicle a in the direction of the resultant force at the curve as:
Figure FDA0003677261220000024
in the formula: f 1 ' is the traction of the vehicle a ahead; f 2 ' is the centripetal force experienced by the vehicle a ahead at a road curve; m A Is the gravity of the preceding vehicle a; a is A Acceleration in the traveling direction of the preceding vehicle a; v. of A The speed of the preceding vehicle a in the traveling direction; theta' is the steering angle of the front vehicle A along the curve; f and' are the resultant force of the centripetal force and the traction force of the front vehicle A at the road curve.
5. The method for establishing a vehicle-following model at a road curve based on a safe potential field theory according to claim 4, wherein in the step 4:
the road potential field model is as follows:
Figure FDA0003677261220000025
in the formula: e S Is road boundary potential field strength; d S Aj A distance vector for the leading vehicle A to point to the road boundary line; d S Aj ＝(y s,j -y A )；y A Is the y-axis coordinate of the front vehicle A; y is s Is the y-axis coordinate of the road line field j; eta is the road boundary field coefficient;
the vehicle potential field model is:
Figure FDA0003677261220000031
in the formula: e V To be automaticThe potential field strength of the driving vehicle B; lambda, beta 1 Are all coefficients; m B Mass of autonomous vehicle B; a is the acceleration of the automatic driving vehicle B in the resultant force direction at the curve;
Figure FDA0003677261220000032
the included angle is the connecting line between the driving direction of the automatic driving vehicle B and the mass center of the front vehicle A; k' is a pseudo distance;
Figure FDA0003677261220000033
theta is a steering angle when the vehicle is steered; (x) * ,y * ) Taking a corresponding deflection value after the original coordinate (x, y) is deflected; τ is a critical threshold for safe distance; v. of B Is the speed of the autonomous vehicle B in the direction of travel; a is a parameter related to speed; (x) 0 ,y 0 ) Coordinates of the center of mass of the autonomous vehicle B.
6. The method for establishing the vehicle-following model at the road curve based on the safe potential field theory according to claim 5, wherein the specific process of the step 5 is as follows:
step 51, according to the safety potential field theory, the magnitude of the potential field force of the front vehicle a on the automatic driving vehicle B is expressed as:
Figure FDA0003677261220000034
in the formula: Δ x is the distance between the center of mass of the autonomous vehicle B and the center of mass of the forward vehicle a; e V ' is the potential field intensity of the front vehicle A; m A Mass of the preceding vehicle a; beta is a 2 Are coefficients.
Step 52, autonomous vehicle B receives F AB Acceleration a generated under the action of AB Comprises the following steps:
Figure FDA0003677261220000035
step 53, automatically driving the acceleration of the vehicle B and F AB The common acceleration a field generated under the action of the magnetic field is as follows:
Figure FDA0003677261220000036
in the formula:
Figure FDA0003677261220000037
the included angle between the driving direction of the front vehicle A and a connecting line between the center of mass of the automatic driving vehicle B and the center of mass of the front vehicle A is included; d AB The distance between the center of mass of the automatic driving vehicle B and the center of mass of the front vehicle A is obtained; mu is a reduction coefficient of the acceleration generated by the potential field force along with the change of the distance;
step 54, a following model of the autonomous vehicle B at the road curve based on the safe potential field theory:
Figure FDA0003677261220000038
Figure FDA0003677261220000041
in the formula: a is max Maximum acceleration for autonomous vehicle B; v. of 0 (a) The expected speed of the automatic driving vehicle B under the condition of acceleration at a certain point of a coordinate axis at a certain moment; δ is a coefficient value of the difference between the current speed and the desired speed of the vehicle.
7. Device for establishing a vehicle-following model at a road curve based on a safe potential field theory, comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method for establishing a vehicle-following model at a road curve based on a safe potential field theory as claimed in any one of claims 1 to 6.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for establishing a vehicle-following model at a road curve based on a safe potential field theory as claimed in any one of claims 1 to 6.
CN202210625677.9A 2022-06-02 2022-06-02 Method for establishing vehicle following model at road curve based on safe potential field theory Pending CN114889625A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115862391A (en) * 2022-11-22 2023-03-28 东南大学 Airport runway vehicle following safety evaluation method oriented to intelligent networking environment
CN116341288A (en) * 2023-05-25 2023-06-27 吉林大学 Heterogeneous traffic epidemic car security field modeling method
CN116645826B (en) * 2023-05-25 2024-04-19 合肥工业大学 Curve following path planning method based on cubic polynomial

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115862391A (en) * 2022-11-22 2023-03-28 东南大学 Airport runway vehicle following safety evaluation method oriented to intelligent networking environment
CN115862391B (en) * 2022-11-22 2023-08-29 东南大学 Airport road car following safety judging method oriented to intelligent networking environment
CN116341288A (en) * 2023-05-25 2023-06-27 吉林大学 Heterogeneous traffic epidemic car security field modeling method
CN116341288B (en) * 2023-05-25 2023-09-05 吉林大学 Heterogeneous traffic epidemic car security field modeling method
CN116645826B (en) * 2023-05-25 2024-04-19 合肥工业大学 Curve following path planning method based on cubic polynomial

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